Linearity is a fundamental requirement in many modern radio systems. It enables the application of increasingly more sophisticated digital signal processing algorithms to increase available data-rates and channel capacity in commercial wireless applications. Furthermore, there exists a relationship between linearity and the ability to apply digital signal processing (DSP) techniques to signals being processed in a radio system. Briefly, the more linear an RF receiver, the higher the level of sophistication which may be used to digitally process the signals. The ability to apply sophisticated DSP techniques is desirable since it leads to increases in available data-rates and channel capacity in applications such as commercial wireless applications.
Linearity is also an important metric in the radar and signal intelligence application space. Thus, as trends towards use of increasingly more advanced algorithms to increase performance in radio systems, linearity becomes correspondingly more important.
At the same time, complementary metal oxide semiconductor (CMOS) scaling poses tremendous difficulties to traditional analog methods of improving system linearity. Available analog dynamic range is limited due to decreasing voltage supplies in modern CMOS as well as the degradation of transistor analog characteristics with each passing generation, making linearity improving circuits such as op-amps, for example, harder to implement with adequate performance. However, since scaling also makes digital circuitry less expensive and more powerful, it becomes meaningful to explore digital nonlinearity compensation as a means to recover at least some performance lost due to nonlinearity of analog circuitry.
Digital receive-side nonlinear compensation has recently become of interest in applications demanding high dynamic range. Some receivers include an analog-to-digital converter (ADC) to quantize an analog signal at an output of the receiver. Thus, if nonlinear distortion introduced by the receiver and ADC can be predicted and recreated based upon observed sampled output via an appropriate nonlinear model, then this recreated distortion can be subtracted away from the original digitized data stream, leading to a corrected output having significantly lower nonlinearity induced distortion.
In bandlimited receiver systems, strong frequency selectivity is required. Thus, such systems include very sharp bandwidth-defining elements such as input band-select filters and intermediate frequency (IF) or baseband filters. Introducing these bandpass elements leads to significant increases in the complexity of a nonlinear compensator. It would therefore, be desirable to provide an efficient technique to deal with this effect in order to satisfactorily implement the digital nonlinearity correction concept.